China Kadoorie Biobank of 0.5 million people: survey methods, baseline characteristics and long-term follow-up

Development and evaluation of a polygenic risk score for lung cancer in never-smoking women: A large-scale prospective Chinese cohort study

The proportion of lung cancer in never smokers is rising, especially among Asian women, but there is no effective early detection tool. Here, we developed a polygenic risk score (PRS), which may help to identify the population with higher risk of lung cancer in never-smoking women. We first performed a large GWAS meta-analysis (8595 cases and 8275 controls) to systematically identify the susceptibility loci for lung cancer in never-smoking Asian women and then generated a PRS using GWAS datasets. Furthermore, we evaluated the utility and effectiveness of PRS in an independent Chinese prospective cohort comprising 55 266 individuals. The GWAS meta-analysis identified eight known loci and a novel locus (5q11.2) at the genome-wide statistical significance level of P < 5 × 10-8 . Based on the summary statistics of GWAS, we derived a polygenic risk score including 21 variants (PRS-21) for lung cancer in never-smoking women. Furthermore, PRS-21 had a hazard ratio (HR) per SD of 1.29 (95% CI = 1.18-1.41) in the prospective cohort. Compared with participants who had a low genetic risk, those with an intermediate (HR = 1.32, 95% CI: 1.00-1.72) and high (HR = 2.09, 95% CI: 1.56-2.80) genetic risk had a significantly higher risk of incident lung cancer. The addition of PRS-21 to the conventional risk model yielded a modest significant improvement in AUC (0.697 to 0.711) and net reclassification improvement (24.2%). The GWAS-derived PRS-21 significantly improves the risk stratification and prediction accuracy for incident lung cancer in never-smoking Asian women, demonstrating the potential for identification of high-risk individuals and early screening.

Benefits and harms of polygenic risk scores in organised cancer screening programmes: a cost-effectiveness analysis

Background

While polygenic risk scores (PRS) could enable the streamlining of organised cancer screening programmes, its current discriminative ability is limited. We conducted a cost-effectiveness analysis to trade-off the benefits and harms of PRS-stratified cancer screening in China.

Methods

The validated National Cancer Center (NCC) modelling framework for six cancers (lung, liver, breast, gastric, colorectum, and oesophagus) was used to simulate cancer incidence, progression, stage-specific cancer detection, and risk of death. We estimated the number of cancer deaths averted, quality-adjusted life-years (QALY) gained, number needed to screen (NNS), overdiagnosis, and incremental cost-effectiveness ratio (ICER) of one-time PRS-stratified screening strategy (screening 25% of PRS-defined high-risk population) for a birth cohort at age 60 in 2025, compared with unstratified screening strategy (screening 25% of general population) and no screening strategy. We applied lifetime horizon, societal perspective, and 3% discount rate. An ICER less than $18,364 per QALY gained is considered cost-effective.

Findings

One-time cancer screening for population aged 60 was the most cost-effective strategy compared to screening at other ages. Compared with an unstratified screening strategy, the PRS-stratified screening strategy averted more cancer deaths (61,237 vs. 40,329), had a lower NNS to prevent one death (307 vs. 451), had a slightly higher overdiagnosis (14.1% vs. 13.8%), and associated with an additional 130,045 QALYs at an additional cost of $1942 million, over a lifetime horizon. The ICER for all six cancers combined was $14,930 per QALY gained, with the ICER varying from $7928 in colorectal cancer to $39,068 in liver cancer. ICER estimates were sensitive to changes in risk threshold and cost of PRS tools.

Interpretation

PRS-stratified screening strategy modestly improves clinical benefit and cost-effectiveness of organised cancer screening programmes. Reducing the costs of polygenic risk stratification is needed before PRS implementation.

Funding

The Chinese Academy of Medical Sciences, the Jing-jin-ji Special Projects for Basic Research Cooperation, and the Sanming Project of the Medicine in Shenzhen.

Correlates and consequences of atrial fibrillation in a prospective study of 25 000 participants in the China Kadoorie Biobank

Aims

The prevalence of atrial fibrillation (AF) is positively correlated with prior cardiovascular diseases (CVD) and CVD risk factors but is lower in Chinese than Europeans despite their higher burden of CVD. We examined the prevalence and prognosis of AF and other electrocardiogram (ECG) abnormalities in the China Kadoorie Biobank.

Methods and results

A random sample of 25 239 adults (mean age 59.5 years, 62% women) had a 12-lead ECG recorded and interpreted using a Mortara VERITAS™ algorithm in 2013-14. Participants were followed up for 5 years for incident stroke, ischaemic heart disease, heart failure (HF), and all CVD, overall and by CHA2DS2-VASc scores, age, sex, and area. Overall, 1.2% had AF, 13.6% had left ventricular hypertrophy (LVH), and 28.1% had ischaemia (two-thirds of AF cases also had ischaemia or LVH). The prevalence of AF increased with age, prior CVD, and levels of CHA₂DS₂-VASc scores (0.5%, 1.3%, 2.1%, 2.9%, and 4.4% for scores <2, 2, 3, 4, and ≥5, respectively). Atrial fibrillation was associated with two-fold higher hazard ratios (HR) for CVD (2.15; 95% CI, 1.71-2.69) and stroke (1.88; 1.44-2.47) and a four-fold higher HR for HF (3.79; 2.21-6.49). The 5-year cumulative incidence of CVD was comparable for AF, prior CVD, and CHA₂DS₂-VASc scores ≥ 2 (36.7% vs. 36.2% vs. 37.7%, respectively) but was two-fold greater than for ischaemia (19.4%), LVH (18.0%), or normal ECG (14.1%), respectively.

Conclusion

The findings highlight the importance of screening for AF together with estimation of CHA₂DS₂-VASc scores for prevention of CVD in Chinese adults.

A systematic review of the performance of actigraphy in measuring sleep stages

The accuracy of actigraphy for sleep staging is assumed to be poor, but examination is limited. This systematic review aimed to assess the performance of actigraphy in sleep stage classification of adults. A systematic search was performed using MEDLINE, Web of Science, Google Scholar, and Embase databases. We identified eight studies that compared sleep architecture estimates between wrist-worn actigraphy and polysomnography. Large heterogeneity was found with respect to how sleep stages were grouped, and the choice of metrics used to evaluate performance. Quantitative synthesis was not possible, so we performed a narrative synthesis of the literature. From the limited number of studies, we found that actigraphy-based sleep staging had some ability to classify different sleep stages compared with polysomnography.

Associations of diabetes, circulating protein biomarkers, and risk of pancreatic cancer

BACKGROUND

Type 2 diabetes (T2D) is associated with higher risk of pancreatic cancer (PC), but the underlying mechanisms are not fully understood.

METHODS

We conducted a case-subcohort study involving 610 PC cases and 623 subcohort participants with 92 protein biomarkers measured in baseline plasma samples. Genetically-instrumented T2D was derived using 86 single-nucleotide polymorphisms (SNPs), including insulin resistance (IR) SNPs.

RESULTS

In observational analyses of 623 subcohort participants (mean age, 52 years; 61% women), T2D was positively associated with 13 proteins (SD difference: IL6: 0.52 [0.23-0.81]; IL10: 0.41 [0.12-0.70]), of which 8 were nominally associated with incident PC. The 8 proteins potentially mediated 36.9% (18.7-75.0%) of the association between T2D and PC. In MR, no associations were observed for genetically-determined T2D with proteins, but there were positive associations of genetically-determined IR with IL6 and IL10 (SD difference: 1.23 [0.05-2.41] and 1.28 [0.31-2.24]). In two-sample MR, fasting insulin was associated with both IL6 and PC, but no association was observed between IL6 and PC.

CONCLUSIONS

Proteomics were likely to explain the association between T2D and PC, but were not causal mediators. Elevated fasting insulin driven by insulin resistance might explain the associations of T2D, proteomics, and PC.

Diabetes and chronic kidney disease in Chinese adults: a population-based cohort study

INTRODUCTION

Cohort evidence of the association of diabetes mellitus (DM) with chronic kidney disease (CKD) is limited. Previous studies often describe patients with kidney disease and diabetes as diabetic kidney disease (DKD) or CKD, ignoring other subtypes. The present study aimed to assess the prospective association of diabetes status (no diabetes, pre-diabetes, screened diabetes, previously diagnosed controlled/uncontrolled diabetes with/without antidiabetic treatment) and random plasma glucose (RPG) with CKD risk (including CKD subtypes) among Chinese adults.

RESEARCH DESIGN AND METHODS

The present study included 472 545 participants from the China Kadoorie Biobank, using baseline information on diabetes and RPG. The incident CKD and its subtypes were collected through linkage with the national health insurance system during follow-up. Cox regression models were used to calculate the HR and 95% CI.

RESULTS

During 11.8 years of mean follow-up, 5417 adults developed CKD. Screened plus previously diagnosed diabetes was positively associated with CKD (HR=4.52, 95% CI 4.23 to 4.83), DKD (HR=33.85, 95% CI 29.56 to 38.76), and glomerulonephritis (HR=1.66, 95% CI 1.40 to 1.97). In those with previously diagnosed diabetes, participants with uncontrolled diabetes represented higher risks of CKD, DKD, and glomerulonephritis compared with those with controlled RPG. The risk of DKD was found to rise in participants with pre-diabetes and increased with the elevated RPG level, even in those without diabetes.

CONCLUSIONS

Among Chinese adults, diabetes was positively associated with CKD, DKD, and glomerulonephritis. Screen-detected and uncontrolled DM had a high risk of CKD, and pre-diabetes was associated with a greater risk of DKD, highlighting the significance of lifelong glycemic management.

Multi-Omic Blood Biomarkers as Dynamic Risk Predictors in Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease is the leading cause of dementia worldwide, accounting for a growing burden of morbidity and mortality. Diagnosing Alzheimer's disease before symptoms are established is clinically challenging, but would provide therapeutic windows for disease-modifying interventions. Blood biomarkers, including genetics, proteins and metabolites, are emerging as powerful predictors of Alzheimer's disease at various timepoints within the disease course, including at the preclinical stage. In this review, we discuss recent advances in such blood biomarkers for determining disease risk. We highlight how leveraging polygenic risk scores, based on genome-wide association studies, can help stratify individuals along their risk profile. We summarize studies analyzing protein biomarkers, as well as report on recent proteomic- and metabolomic-based prediction models. Finally, we discuss how a combination of multi-omic blood biomarkers can potentially be used in memory clinics for diagnosis and to assess the dynamic risk an individual has for developing Alzheimer's disease dementia.

Prospective study design and data analysis in UK Biobank

Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank's study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide.

Lifetime cumulative effect of reproductive factors on ischaemic heart disease in a prospective cohort

OBJECTIVE

This study aimed to examine the association between lifetime oestrogen exposure and ischaemic heart disease (IHD), based on the hypothesis that higher lifetime oestrogen exposure is linked to lower cardiovascular risk.

METHODS

In 2004-2008, lifetime cumulative exposure to reproductive factors was assessed among postmenopausal females from the China Kadoorie Biobank using reproductive lifespan (RLS), endogenous oestrogen exposure (EEE) and total oestrogen exposure (TEE). EEE was calculated by subtracting pregnancy-related and contraceptive use duration from RLS, while TEE by adding up the same components except for lactation. Incident IHD during follow-up (2004-2015) was identified. Stratified Cox proportional hazards models estimated the HRs and 95% CIs of IHD for RLS, EEE and TEE.

RESULTS

Among 118 855 postmenopausal females, 13 162 (11.1%) developed IHD during a median follow-up of 8.9 years. The IHD incidence rates were 13.0, 12.1, 12.5, 13.8 per 1000 person-years for RLS Q1-Q4, 15.8, 12.6, 11.3, 12.1 per 1000 person-years for EEE Q1-Q4 and 13.7, 12.3, 12.2, 13.4 per 1000 person-years for TEE Q1-Q4. The highest quartile (Q4) of RLS and TEE were associated with lower risks of IHD (adjusted HR (aHR) 0.95, 95% CI 0.91 to 1.00 and 0.92, 95% CI 0.88 to 0.97, respectively) compared with the lowest quartile (Q1). Longer EEE showed progressively lower risks of incident IHD (aHR 0.93, 95% CI 0.88 to 0.97; 0.88, 95% CI 0.84 to 0.93; 0.87, 95% CI 0.83 to 0.92 for Q2-Q4 vs Q1).

CONCLUSIONS

Longer RLS, TEE and EEE were associated with lower risks of IHD among Chinese postmenopausal females.

PGS-Depot: a comprehensive resource for polygenic scores constructed by summary statistics based methods

Polygenic score (PGS) is an important tool for the genetic prediction of complex traits. However, there are currently no resources providing comprehensive PGSs computed from published summary statistics, and it is difficult to implement and run different PGS methods due to the complexity of their pipelines and parameter settings. To address these issues, we introduce a new resource called PGS-Depot containing the most comprehensive set of publicly available disease-related GWAS summary statistics. PGS-Depot includes 5585 high quality summary statistics (1933 quantitative and 3652 binary trait statistics) curated from 1564 traits in European and East Asian populations. A standardized best-practice pipeline is used to implement 11 summary statistics-based PGS methods, each with different model assumptions and estimation procedures. The prediction performance of each method can be compared for both in- and cross-ancestry populations, and users can also submit their own summary statistics to obtain custom PGS with the available methods. Other features include searching for PGSs by trait name, publication, cohort information, population, or the MeSH ontology tree and searching for trait descriptions with the experimental factor ontology (EFO). All scores, SNP effect sizes and summary statistics can be downloaded via FTP. PGS-Depot is freely available at http://www.pgsdepot.net.

A wide landscape of morbidity and mortality risk associated with marital status in 0.5 million Chinese men and women: a prospective cohort study

Background

A comprehensive depiction of long-term health impacts of marital status is lacking.

Methods

Sex-stratified phenome-wide association analyses (PheWAS) of marital status (living with vs. without a spouse) were performed using baseline (2004-2008) and follow-up information (ICD10-coded events till Dec 31, 2017) from the China Kadoorie Biobank (CKB). We estimated adjusted hazard ratios (aHRs) to evaluate the associations of marital status with morbidity risks of phenome-wide significant diseases or sex-specific top-10 death causes in China documented in 2017. Additionally, the association between marital status and mortality risks among participants with major chronic diseases at baseline was assessed.

Findings

During up to 11.1 years of the median follow-up period, 1,946,380 incident health events were recorded among 210,202 men and 302,521 women aged 30-79. Marital status was found to have phenome-wide significant associations with thirteen diseases among men (p < 9.92 × 10-5) and nine diseases among women (p < 9.33 × 10-5), respectively. After adjusting for all disease-specific covariates in the final model, participants living without a spouse showed increased risks of schizophrenia, schizotypal and delusional disorders (aHR [95% CI]: 2.55, [1.83-3.56] for men; 1.49, [1.13-1.97] for women) compared with their counterparts. Additional higher risks in overall mental and behavioural disorder (1.31, 1.13-1.53), cardiovascular disease (1.07, 1.04-1.10) and cancer (1.06, 1.00-1.12) were only observed among men without a spouse, whereas women living without a spouse were at lower risks of developing genitourinary diseases (0.89, 0.85-0.93) and injury & poisoning (0.93, 0.88-0.97). Among 282,810 participants with major chronic diseases at baseline, 39,166 deaths were recorded. Increased mortality risks for those without a spouse were observed in 12 of 21 diseases among male patients and one of 23 among female patients. For patients with any self-reported disease at baseline, compared with those living with a spouse, the aHRs (95% CIs) of mortality risk were 1.29 (1.24-1.34) and 1.04 (1.00-1.07) among men and women without a spouse (pinteraction<0.0001), respectively.

Interpretation

Long-term associations of marital status with morbidity and mortality risks are diverse among middle-aged Chinese adults, and the adverse impacts due to living without a spouse are more profound among men. Marital status may be an influential factor for health needs.

Funding

The National Natural Science Foundation of China, the Kadoorie Charitable Foundation, the National Key R&D Program of China, the Chinese Ministry of Science and Technology, and the UK Wellcome Trust.

Machine Learning to Advance Human Genome-Wide Association Studies

Machine learning, including deep learning, reinforcement learning, and generative artificial intelligence are revolutionising every area of our lives when data are made available. With the help of these methods, we can decipher information from larger datasets while addressing the complex nature of biological systems in a more efficient way. Although machine learning methods have been introduced to human genetic epidemiological research as early as 2004, those were never used to their full capacity. In this review, we outline some of the main applications of machine learning to assigning human genetic loci to health outcomes. We summarise widely used methods and discuss their advantages and challenges. We also identify several tools, such as Combi, GenNet, and GMSTool, specifically designed to integrate these methods for hypothesis-free analysis of genetic variation data. We elaborate on the additional value and limitations of these tools from a geneticist's perspective. Finally, we discuss the fast-moving field of foundation models and large multi-modal omics biobank initiatives.

MTHFR and risk of stroke and heart disease in a low-folate population: a prospective study of 156 000 Chinese adults

BACKGROUND

The relevance of folic acid for stroke prevention in low-folate populations such as in China is uncertain. Genetic studies of the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism, which increases plasma homocysteine (tHcy) levels, could clarify the causal relevance of elevated tHcy levels for stroke, ischaemic heart disease (IHD) and other diseases in populations without folic acid fortification.

METHODS

In the prospective China Kadoorie Biobank, 156 253 participants were genotyped for MTHFR and 12 240 developed a stroke during the 12-year follow-up. Logistic regression was used to estimate region-specific odds ratios (ORs) for total stroke and stroke types, IHD and other diseases comparing TT genotype for MTHFR C677T (two thymine alleles at position 677 of MTHFR C677T polymorphism) vs CC (two cytosine alleles) after adjustment for age and sex, and these were combined using inverse-variance weighting.

RESULTS

Overall, 21% of participants had TT genotypes, but this varied from 5% to 41% across the 10 study regions. Individuals with TT genotypes had 13% (adjusted OR 1.13, 95% CI 1.09-1.17) higher risks of any stroke [with a 2-fold stronger association with intracerebral haemorrhage (1.24, 1.17-1.32) than for ischaemic stroke (1.11, 1.07-1.15)] than the reference CC genotype. In contrast, MTHFR C677T was unrelated to risk of IHD or any other non-vascular diseases, including cancer, diabetes and chronic obstructive lung disease.

CONCLUSIONS

In Chinese adults, the MTHFR C677T polymorphism was associated with higher risks of stroke. The findings warrant corroboration by further trials of folic acid and implementation of mandatory folic acid fortification programmes for stroke prevention in low-folate populations.

Ethnic differences of genetic risk and smoking in lung cancer: two prospective cohort studies

BACKGROUND

The role of genetic background underlying the disparity of relative risk of smoking and lung cancer between European populations and East Asians remains unclear.

METHODS

To assess the role of ethnic differences in genetic factors associated with smoking-related risk of lung cancer, we first constructed ethnic-specific polygenic risk scores (PRSs) to quantify individual genetic risk of lung cancer in Chinese and European populations. Then, we compared genetic risk and smoking as well as their interactions on lung cancer between two cohorts, including the China Kadoorie Biobank (CKB) and the UK Biobank (UKB). We also evaluated the absolute risk reduction over a 5-year period.

RESULTS

Differences in compositions and association effects were observed between the Chinese-specific PRSs and European-specific PRSs, especially for smoking-related loci. The PRSs were consistently associated with lung cancer risk, but stronger associations were observed in smokers of the UKB [hazard ratio (HR) 1.26 vs 1.15, P  =  0.028]. A significant interaction between genetic risk and smoking on lung cancer was observed in the UKB (RERI, 11.39 (95% CI, 7.01-17.94)], but not in the CKB. Obvious higher absolute risk was observed in nonsmokers of the CKB, and a greater absolute risk reduction was found in the UKB (10.95 vs 7.12 per 1000 person-years, P <0.001) by comparing heavy smokers with nonsmokers, especially for those at high genetic risk.

CONCLUSIONS

Ethnic differences in genetic factors and the high incidence of lung cancer in nonsmokers of East Asian ethnicity were involved in the disparity of smoking-related risk of lung cancer.

Characterising personal, household, and community PM2.5 exposure in one urban and two rural communities in China

BACKGROUND

Cooking and heating in households contribute importantly to air pollution exposure worldwide. However, there is insufficient investigation of measured fine particulate matter (PM2.5) exposure levels, variability, seasonality, and inter-spatial dynamics associated with these behaviours.

METHODS

We undertook parallel measurements of personal, household (kitchen and living room), and community PM2.5 in summer (May-September 2017) and winter (November 2017-Janauary 2018) in 477 participants from one urban and two rural communities in China. After stringent data cleaning, there were 67,326-80,980 person-hours (ntotal = 441; nsummer = 384; nwinter = 364; 307 had repeated PM2.5 data in both seasons) of processed data per microenvironment. Age- and sex-adjusted geometric means of PM2.5 were calculated by key participant characteristics, overall and by season. Spearman correlation coefficients between PM2.5 levels across different microenvironments were computed.

FINDINGS

Overall, 26.4 % reported use of solid fuel for both cooking and heating. Solid fuel users had 92 % higher personal and kitchen 24-h average PM2.5 exposure than clean fuel users. Similarly, they also had a greater increase (83 % vs 26 %) in personal and household PM2.5 from summer to winter, whereas community levels of PM2.5 were 2-4 times higher in winter across different fuel categories. Compared with clean fuel users, solid fuel users had markedly higher weighted annual average PM2.5 exposure at personal (78.2 [95 % CI 71.6-85.3] μg/m3 vs 41.6 [37.3-46.5] μg/m3), kitchen (102.4 [90.4-116.0] μg/m3 vs 52.3 [44.8-61.2] μg/m3) and living room (62.1 [57.3-67.3] μg/m3 vs 41.0 [37.1-45.3] μg/m3) microenvironments. There was a remarkable diurnal variability in PM2.5 exposure among the participants, with 5-min moving average from 10 μg/m3 to 700-1200 μg/m3 across different microenvironments. Personal PM2.5 was moderately correlated with living room (Spearman r: 0.64-0.66) and kitchen (0.52-0.59) levels, but only weakly correlated with community levels, especially in summer (0.15-0.34) and among solid fuel users (0.11-0.31).

CONCLUSION

Solid fuel use for cooking and heating was associated with substantially higher personal and household PM2.5 exposure than clean fuel users. Household PM2.5 appeared a better proxy of personal exposure than community PM2.5.

Binge-pattern alcohol consumption and genetic risk as determinants of alcohol-related liver disease

Alcohol-related liver disease (ARLD) represents a major public health burden. Identification of high-risk individuals would allow efficient targeting of public health interventions. Here, we show significant interactions between pattern of drinking, genetic predisposition (polygenic risk score, PRS) and diabetes mellitus, and risk of incident ARLD, in 312,599 actively drinking adults in UK Biobank. Binge and heavy binge drinking significantly increase the risk of alcohol-related cirrhosis (ARC), with higher genetic predisposition further amplifying the risk. Further, we demonstrate a pronounced interaction between heavy binge drinking and high PRS, resulting in a relative excess risk due to interaction (RERI) of 6.07. Diabetes consistently elevates ARC risk across all drinking and PRS categories, and showed significant interaction with both binge patterns and genetic risk. Overall, we demonstrate synergistic effects of binge drinking, genetics, and diabetes on ARC, with potential to identify high-risk individuals for targeted interventions.

Increasing diversity of functional genetics studies to advance biological discovery and human health

In this perspective we discuss the current lack of genetic and environmental diversity in functional genomics datasets. There is a well-described Eurocentric bias in genetic and functional genomic research that has a clear impact on the benefit this research can bring to underrepresented populations. Current research focused on genetic variant-to-function experiments aims to identify molecular QTLs, but the lack of data from genetically diverse individuals has limited analyses to mostly populations of European ancestry. Although some efforts have been established to increase diversity in functional genomic studies, much remains to be done to consistently generate data for underrepresented populations from now on. We discuss the major barriers for this continuity and suggest actionable insights, aiming to empower research and researchers from underserved populations.

Artificial intelligence for dementia-Applied models and digital health

INTRODUCTION

The use of applied modeling in dementia risk prediction, diagnosis, and prognostics will have substantial public health benefits, particularly as "deep phenotyping" cohorts with multi-omics health data become available.

METHODS

This narrative review synthesizes understanding of applied models and digital health technologies, in terms of dementia risk prediction, diagnostic discrimination, prognosis, and progression. Machine learning approaches show evidence of improved predictive power compared to standard clinical risk scores in predicting dementia, and the potential to decompose large numbers of variables into relatively few critical predictors.

RESULTS

This review focuses on key areas of emerging promise including: emphasis on easier, more transparent data sharing and cohort access; integration of high-throughput biomarker and electronic health record data into modeling; and progressing beyond the primary prediction of dementia to secondary outcomes, for example, treatment response and physical health.

DISCUSSION

Such approaches will benefit also from improvements in remote data measurement, whether cognitive (e.g., online), or naturalistic (e.g., watch-based accelerometry).

Interplay between oral health and lifestyle factors for cancer risk in rural and urban China: a population-based cohort study

Background

Although poor oral health and several lifestyle factors have been found to be associated with cancer risk, their joint relationship has rarely been studied.

Methods

We prospectively examined the associations of oral health and healthy lifestyle factors with cancer risk among 0.5 million rural and urban residents from the China Kadoorie Biobank (2004-2015). Oral health status was assessed from self-reported baseline questionnaires. A healthy lifestyle index comprising non-smoking, non-drinking, ideal body shape, physical activity and healthy diet was calculated for each participant, and categorized into favorable, intermediate and unfavorable lifestyle behavior. We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) relating oral health and healthy lifestyle index to cancer risk using Cox proportional hazards models. We estimated the population attributable risk percent (PAR%) and 95% CIs using multivariate models.

Results

During a median follow-up of 9 years, 23,805 new cancer cases were documented, with 52% from rural areas and 48% from urban areas. Compared with those with good oral health and favorable lifestyle, participants with poor oral health and unfavorable lifestyle had a higher risk of developing cancer in both rural (adjusted HR, 1.55 [95% CI, 1.39-1.74]; P for trend < 0.001) and urban areas (adjusted HR, 1.44 [95% CI, 1.24-1.67]; P for trend < 0.001). A significant multiplicative interaction between oral health and healthy lifestyle index on cancer risk was found in rural residents (P for interaction = 0.004) rather than in urban residents (P for interaction = 0.973). Assuming poor oral health as an additional risk factor, the PAR% of total cancer increased by 3.0% and 1.1% for participants with intermediate lifestyle and unfavorable lifestyle, respectively.

Conclusions

These findings suggest a joint effect of oral health and common lifestyle factors on cancer risk. Promotion of healthy lifestyle by integration of good oral health would be beneficial to consider in cancer prevention strategies.

Alcohol intake and cause-specific mortality: conventional and genetic evidence in a prospective cohort study of 512 000 adults in China

BACKGROUND

Genetic variants that affect alcohol use in East Asian populations could help assess the causal effects of alcohol consumption on cause-specific mortality. We aimed to investigate the associations between alcohol intake and cause-specific mortality using conventional and genetic epidemiological methods among more than 512 000 adults in China.

METHODS

The prospective China Kadoorie Biobank cohort study enrolled 512 724 adults (210 205 men and 302 519 women) aged 30-79 years, during 2004-08. Residents with no major disabilities from ten diverse urban and rural areas of China were invited to participate, and alcohol use was self-reported. During 12 years of follow-up, 56 550 deaths were recorded through linkage to death registries, including 23 457 deaths among 168 050 participants genotyped for ALDH2-rs671 and ADH1B-rs1229984. Adjusted hazard ratios (HRs) for cause-specific mortality by self-reported and genotype-predicted alcohol intake were estimated using Cox regression.

FINDINGS

33% of men drank alcohol most weeks. In conventional observational analyses, ex-drinkers, non-drinkers, and heavy drinkers had higher risks of death from most major causes than moderate drinkers. Among current drinkers, each 100 g/week higher alcohol intake was associated with higher mortality risks from cancers (HR 1·18 [95% CI 1·14-1·22]), cardiovascular disease (CVD; HR 1·19 [1·15-1·24]), liver diseases (HR 1·51 [1·27-1·78]), non-medical causes (HR 1·15 [1·08-1·23]), and all causes (HR 1·18 [1·15-1·20]). In men, ALDH2-rs671 and ADH1B-rs1229984 genotypes predicted 60-fold differences in mean alcohol intake (4 g/week in the lowest group vs 255 g/week in the highest). Genotype-predicted alcohol intake was uniformly and positively associated with risks of death from all causes (n=12 939; HR 1·07 [95% CI 1·05-1·10]) and from pre-defined alcohol-related cancers (n=1274; 1·12 [1·04-1·21]), liver diseases (n=110; 1·31 [1·02-1·69]), and CVD (n=6109; 1·15 [1·10-1·19]), chiefly due to stroke (n=3285; 1·18 [1·12-1·24]) rather than ischaemic heart disease (n=2363; 1·06 [0·99-1·14]). Results were largely consistent using a polygenic score to predict alcohol intake, with higher intakes associated with higher risks of death from alcohol-related cancers, CVD, and all causes. Approximately 2% of women were current drinkers, and although power was low to assess observational associations of alcohol with mortality, the genetic evidence suggested that the excess risks in men were due to alcohol, not pleiotropy.

INTERPRETATION

Higher alcohol intake increased the risks of death overall and from major diseases for men in China. There was no genetic evidence of protection from moderate drinking for all-cause and cause-specific mortality, including CVD.

FUNDING

Kadoorie Charitable Foundation, National Natural Science Foundation of China, British Heart Foundation, Cancer Research UK, GlaxoSmithKline, Wellcome Trust, Medical Research Council, and Chinese Ministry of Science and Technology.

Life-course adiposity and severe liver disease: a Mendelian randomization analysis

OBJECTIVE

There is little evidence on the genetic associations between life-course adiposity (including birth weight, childhood BMI, and adulthood BMI) and severe liver disease (SLD; including cirrhosis and liver cancer). The current study aimed to examine and contrast these associations.

METHODS

Genetic variants were obtained from genome-wide association studies. Two-sample Mendelian randomization (MR) analyses were performed to assess the genetic associations of life-course adiposity with SLD and liver biomarkers. Cox regression was used to estimate adjusted hazard ratios for SLD associated with genetic risk scores of life-course adiposity and adulthood weight change in the China Kadoorie Biobank.

RESULTS

In observational analyses, genetic predispositions to childhood adiposity and adulthood adiposity were each associated with SLD. There was a U-shaped association between adulthood weight change and risk of SLD. In meta-analyses of MR results, genetically predicted 1-standard deviation increase in birth weight was inversely associated with SLD at a marginal significance (odds ratio: 0.81 [95% CI: 0.65-1.00]), whereas genetically predicted 1-standard deviation higher childhood BMI and adulthood BMI were positively associated with SLD (odds ratio: 1.27 [95% CI: 1.05-1.55] and 1.79 [95% CI: 1.59-2.01], respectively). The results of liver biomarkers mirrored those of SLD.

CONCLUSIONS

The current study provided genetic evidence on the associations between life-course adiposity and SLD.

Chronic Hepatitis B Virus Infection and Risk of Stroke Types: A Prospective Cohort Study of 500 000 Chinese Adults

BACKGROUND

Stroke is a leading cause of mortality and permanent disability in China, with large and unexplained geographic variations in rates of different stroke types. Chronic hepatitis B virus infection is prevalent among Chinese adults and may play a role in stroke cause.

METHODS

The prospective China Kadoorie Biobank included >500 000 adults aged 30 to 79 years who were recruited from 10 (5 urban and 5 rural) geographically diverse areas of China from 2004 to 2008, with determination of hepatitis B surface antigen (HBsAg) positivity at baseline. During 11 years of follow-up, a total of 59 117 incident stroke cases occurred, including 11 318 intracerebral hemorrhage (ICH), 49 971 ischemic stroke, 995 subarachnoid hemorrhage, and 3036 other/unspecified stroke. Cox regression models were used to estimate adjusted hazard ratios (HRs) for risk of stroke types associated with HBsAg positivity. In a subset of 17 833 participants, liver enzymes and lipids levels were measured and compared by HBsAg status.

RESULTS

Overall, 3.0% of participants were positive for HBsAg. HBsAg positivity was associated with an increased risk of ICH (adjusted HR, 1.29 [95% CI, 1.16-1.44]), similarly for fatal (n=5982; adjusted HR, 1.36 [95% CI, 1.16-1.59]) and nonfatal (n=5336; adjusted HR, 1.23 [95% CI, 1.06-1.44]) ICH. There were no significant associations of HBsAg positivity with risks of ischemic stroke (adjusted HR, 0.97 [95% CI, 0.92-1.03]), subarachnoid hemorrhage (adjusted HR, 0.87 [95% CI, 0.57-1.33]), or other/unspecified stroke (adjusted HR, 1.12 [95% CI, 0.89-1.42]). Compared with HBsAg-negative counterparts, HBsAg-positive individuals had lower lipid and albumin levels and higher liver enzyme levels. After adjustment for liver enzymes and albumin, the association with ICH from HBsAg positivity attenuated to 1.15 (0.90-1.48), suggesting possible mediation by abnormal liver function.

CONCLUSIONS

Among Chinese adults, chronic hepatitis B virus infection is associated with an increased risk of ICH but not other stroke types, which may be mediated through liver dysfunction and altered lipid metabolism.

Associations between experience of stressful life events and cancer prevalence in China: results from the China Kadoorie Biobank study

BACKGROUND

Studies examining the relationships of stressful life events and cancer yielded inconsistent findings, while relevant evidence in mainland China is scarce. The current study sought to determine whether experience of stressful life events was associated with cancer prevalence in Chinese population.

METHODS

We used cross-sectional data from the China Kadoorie Biobank study which that recruited 0.5 million Chinese adults aged 30 to 79 from 2004 to 2008. Logistic regression models were used to estimate adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for cancer associated with stressful life events reported at baseline.

RESULTS

Among the 461,696 participants included in this analysis, 2,122 (0.46%) had self-reported cancer with the mean (SD) age was 57.12 (9.71) years. Compared to those without any stressful life event, participants who experienced 1 and 2 or more events had significantly higher odds of cancer, with the ORs of 1.80 (95% CI: 1.58-2.05) and 3.05 (2.18-4.28). For categories of work-, family-, and personal-related events, the OR of cancer was 1.48 (1.07-2.05), 2.06 (1.80-2.35), and 1.65 (1.17-2.33), respectively. Regarding the specific stressful life events, loss of income/living on debt, major conflict within family, death/major illness of other close family member, and major injury/traffic accident were significantly associated with increased odds of cancer, with the ORs of 2.64 (1.81-3.86), 1.73 (1.20-2.50), 2.36 (2.05-2.72), and 2.11 (1.43-3.13).

CONCLUSION

Our findings suggested that experiences of cumulative and specific stressful life events were significantly associated with increased cancer prevalence in Chinese population.

Systems genetics approaches for understanding complex traits with relevance for human disease

Quantitative traits are often complex because of the contribution of many loci, with further complexity added by environmental factors. In medical research, systems genetics is a powerful approach for the study of complex traits, as it integrates intermediate phenotypes, such as RNA, protein, and metabolite levels, to understand molecular and physiological phenotypes linking discrete DNA sequence variation to complex clinical and physiological traits. The primary purpose of this review is to describe some of the resources and tools of systems genetics in humans and rodent models, so that researchers in many areas of biology and medicine can make use of the data.

Plasma Proteomics to Identify Drug Targets for Ischemic Heart Disease

BACKGROUND

Integrated analyses of plasma proteomic and genetic markers in prospective studies can clarify the causal relevance of proteins and discover novel targets for ischemic heart disease (IHD) and other diseases.

OBJECTIVES

The purpose of this study was to examine associations of proteomics and genetics data with IHD in population studies to discover novel preventive treatments.

METHODS

We conducted a nested case-cohort study in the China Kadoorie Biobank (CKB) involving 1,971 incident IHD cases and 2,001 subcohort participants who were genotyped and free of prior cardiovascular disease. We measured 1,463 proteins in the stored baseline samples using the OLINK EXPLORE panel. Cox regression yielded adjusted HRs for IHD associated with individual proteins after accounting for multiple testing. Moreover, cis-protein quantitative loci (pQTLs) identified for proteins in genome-wide association studies of CKB and of UK Biobank were used as instrumental variables in separate 2-sample Mendelian randomization (MR) studies involving global CARDIOGRAM+C4D consortium (210,842 IHD cases and 1,378,170 controls).

RESULTS

Overall 361 proteins were significantly associated at false discovery rate <0.05 with risk of IHD (349 positively, 12 inversely) in CKB, including N-terminal prohormone of brain natriuretic peptide and proprotein convertase subtilisin/kexin type 9. Of these 361 proteins, 212 had cis-pQTLs in CKB, and MR analyses of 198 variants in CARDIOGRAM+C4D identified 13 proteins that showed potentially causal associations with IHD. Independent MR analyses of 307 cis-pQTLs identified in Europeans replicated associations for 4 proteins (FURIN, proteinase-activated receptor-1, Asialoglycoprotein receptor-1, and matrix metalloproteinase-3). Further downstream analyses showed that FURIN, which is highly expressed in endothelial cells, is a potential novel target and matrix metalloproteinase-3 a potential repurposing target for IHD.

CONCLUSIONS

Integrated analyses of proteomic and genetic data in Chinese and European adults provided causal support for FURIN and multiple other proteins as potential novel drug targets for treatment of IHD.

Ethnic Differences in the Association Between Age at Natural Menopause and Risk of Type 2 Diabetes Among Postmenopausal Women: A Pooled Analysis of Individual Data From 13 Cohort Studies

OBJECTIVE

To investigate associations between age at natural menopause, particularly premature ovarian insufficiency (POI) (natural menopause before age 40 years), and incident type 2 diabetes (T2D) and identify any variations by ethnicity.

RESEARCH DESIGN AND METHODS

We pooled individual-level data of 338,059 women from 13 cohort studies without T2D before menopause from six ethnic groups: White (n = 177,674), Chinese (n = 146,008), Japanese (n = 9,061), South/Southeast Asian (n = 2,228), Black (n = 1,838), and mixed/other (n = 1,250). Hazard ratios (HRs) of T2D associated with age at menopause were estimated in the overall sample and by ethnicity, with study as a random effect. For each ethnic group, we further stratified the association by birth year, education level, and BMI.

RESULTS

Over 9 years of follow-up, 20,064 (5.9%) women developed T2D. Overall, POI (vs. menopause at age 50-51 years) was associated with an increased risk of T2D (HR 1.31; 95% CI 1.20-1.44), and there was an interaction between age at menopause and ethnicity (P < 0.0001). T2D risk associated with POI was higher in White (1.53; 1.36-1.73), Japanese (4.04; 1.97-8.27), and Chinese women born in 1950 or later (2.79; 2.11-3.70); although less precise, the risk estimates were consistent in women of South/Southeast Asian (1.46; 0.89-2.40), Black (1.72; 0.95-3.12), and mixed/other (2.16; 0.83-5.57) ethnic groups. A similar pattern, but with a smaller increased risk of T2D, was observed with early menopause overall (1.16; 1.10-1.23) and for White, Japanese, and Chinese women born in 1950 or later.

CONCLUSIONS

POI and early menopause are risk factors for T2D in postmenopausal women, with considerable variation across ethnic groups, and may need to be considered in risk assessments of T2D among women.

Pulse pressure and its association with body composition among Chinese men and women without diagnosed hypertension: the China Kadoorie Biobank

BACKGROUND

Wide brachial pulse pressure (PP) has been associated with cardiovascular events, while its population distribution and association with body composition were poorly characterized in large populations.

METHODS

We evaluated the age and sex distributions of PP and its associations with body composition using baseline data from the China Kadoorie Biobank. A total of 434 200 participants without diagnosed hypertension were included in the analysis. Wide PP was defined as PP above 65 mmHg. Body composition variables, including BMI, waist circumference, waist-to-hip ratio (WHR), fat mass index (FMI), fat-free mass index (FFMI), and body fat percentage (BF%), were obtained from bioelectrical impedance analysis.

RESULTS

Overall, 14.3% of the participants had wide PP. Older age was consistently associated with wider PP in women but only after the andropause stage in men. The independent associations of BMI with wide PP were stronger than other body composition measures. The adjusted differences (men/women, mmHg) in PP per standard deviation (SD) increase in BMI (1.55/1.47) were higher than other body composition (BF%: 0.32/0.64, waist circumference: 0.33/0.39; WHR: 0.49/0.42). In addition, sex differences were observed. In men, the per SD difference in PP was higher for FFMI than for FMI (0.91 vs. 0.67, P  < 0.05), whereas in women, it was higher for FMI than for FFMI (1.01 vs. 0.72, P  < 0.05).

CONCLUSION

Our nationwide population-based study presented the sex-specific distribution of PP over age and identified differential associations of PP with fat and fat-free mass in men and women.

Household air pollution and risk of incident lung cancer in urban China: A prospective cohort study

Household air pollution (HAP) is associated with the development of lung cancer, yet few studies investigated the exposure patterns and joint associations with tobacco smoking. In our study, we included 224 189 urban participants from China Kadoorie Biobank (CKB), 3288 of which diagnosed with lung cancer during the follow-up. Exposure to four HAP sources (solid fuels for cooking/heating/stove and environmental tobacco smoke exposure) was assessed at baseline. Distinct HAP patterns and their associations with lung cancer were examined through latent class analysis (LCA) and multivariable Cox regression. A total of 76.1% of the participants reported regular cooking and 52.2% reported winter heating, of which 9% and 24.7% used solid fuels, respectively. Solid fuel heating increased lung cancer risk (Hazards ratio [HR]: 1.25, 95% confidence interval [CI]: 1.08-1.46). LCA identified three HAP patterns; the "clean fuel cooking and solid fuel heating" pattern significantly increased lung cancer risk (HR: 1.25, 95% CI: 1.10-1.41), compared to low HAP pattern. An additive interaction was observed between heavy smoking and "clean fuel cooking and solid fuel heating" (relative excess risk [RERI]: 1.32, 95% CI: 0.29-2.47, attributable proportion [AP]: 0.23, 95% CI: 0.06-0.36). Cases resulting from solid fuel account for ~4% of total cases (population attribute fraction [PAF]overall : 4.31%, 95% CI: 2.16%-6.47%, PAFever smokers : 4.38%, 95% CI: 1.54%-7.23%). Our results suggest that in urban China, solid fuel heating increased the risk of lung cancer, particularly among heavy smokers. The whole population could benefit from cleaner indoor air quality by reducing using solid fuels, especially smokers.

Pragmatic Approach to Applying Polygenic Risk Scores to Diverse Populations

Polygenic risk scores (PRS) estimate genetic susceptibility of an individual to disease and have the potential of providing utility in multiple clinical contexts. However, their performance, computation, and reporting in diverse populations remain challenging. Here, we present a pragmatic approach to optimize a PRS for a population of interest that leverages publicly available data and methods and consists of seven steps that are easily implemented without the requirement of expertise in complex genetics: step 1, selecting source genome-wide association studies (GWAS) and imputation; step 2, selecting methods to compute polygenic score; step 3, adjusting scores using principal components of genetic ancestry; step 4, selecting the best performing score; step 5, defining percentiles of a population distribution; step 6, validating performance of the optimized polygenic score; and step 7, implementing the optimized polygenic score in clinical practice. © 2023 Wiley Periodicals LLC.

Genetic influences on alcohol flushing in East Asian populations

BACKGROUND

Although it is known that variation in the aldehyde dehydrogenase 2 (ALDH2) gene family influences the East Asian alcohol flushing response, knowledge about other genetic variants that affect flushing symptoms is limited.

METHODS

We performed a genome-wide association study meta-analysis and heritability analysis of alcohol flushing in 15,105 males of East Asian ancestry (Koreans and Chinese) to identify genetic associations with alcohol flushing. We also evaluated whether self-reported flushing can be used as an instrumental variable for alcohol intake.

RESULTS

We identified variants in the region of ALDH2 strongly associated with alcohol flushing, replicating previous studies conducted in East Asian populations. Additionally, we identified variants in the alcohol dehydrogenase 1B (ADH1B) gene region associated with alcohol flushing. Several novel variants were identified after adjustment for the lead variants (ALDH2-rs671 and ADH1B-rs1229984), which need to be confirmed in larger studies. The estimated SNP-heritability on the liability scale was 13% (S.E. = 4%) for flushing, but the heritability estimate decreased to 6% (S.E. = 4%) when the effects of the lead variants were controlled for. Genetic instrumentation of higher alcohol intake using these variants recapitulated known associations of alcohol intake with hypertension. Using self-reported alcohol flushing as an instrument gave a similar association pattern of higher alcohol intake and cardiovascular disease-related traits (e.g. stroke).

CONCLUSION

This study confirms that ALDH2-rs671 and ADH1B-rs1229984 are associated with alcohol flushing in East Asian populations. Our findings also suggest that self-reported alcohol flushing can be used as an instrumental variable in future studies of alcohol consumption.

Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores: evidence from the China Kadoorie Biobank

BACKGROUND

Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population.

METHODS

Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training ( n = 28,490) and testing sets ( n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21-I23 and fatal I20-I25) and soft CAD (all fatal or nonfatal I20-I25) were analyzed separately.

RESULTS

In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19-1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (-0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4-6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model.

CONCLUSIONS

In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.

Influence of Socioeconomic Gender Inequality on Sex Disparities in Prevention and Outcome of Cardiovascular Disease: Data From a Nationwide Population Cohort in China

Background Knowledge gaps remain in how gender-related socioeconomic inequality affects sex disparities in cardiovascular diseases (CVD) prevention and outcome. Methods and Results Based on a nationwide population cohort, we enrolled 3 737 036 residents aged 35 to 75 years (2014-2021). Age-standardized sex differences and the effect of gender-related socioeconomic inequality (Gender Inequality Index) on sex disparities were explored in 9 CVD prevention indicators. Compared with men, women had seemingly better primary prevention (aspirin usage: relative risk [RR], 1.24 [95% CI, 1.18-1.31] and statin usage: RR, 1.48 [95% CI, 1.39-1.57]); however, women's status became insignificant or even worse when adjusted for metabolic factors. In secondary prevention, the sex disparities in usage of aspirin (RR, 0.65 [95% CI, 0.63-0.68]) and statin (RR, 0.63 [95% CI, 0.61-0.66]) were explicitly larger than disparities in usage of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (RR, 0.88 [95% CI, 0.84-0.91]) or β blockers (RR, 0.67 [95% CI, 0.63-0.71]). Nevertheless, women had better hypertension awareness (RR, 1.09 [95% CI, 1.09-1.10]), similar hypertension control (RR, 1.01 [95% CI, 1.00-1.02]), and lower CVD mortality (hazard ratio, 0.46 [95% CI, 0.45-0.47]). Heterogeneities of sex disparities existed across all subgroups. Significant correlations existed between regional Gender Inequality Index values and sex disparities in usage of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (Spearman correlation coefficient, r=-0.57, P=0.0013), hypertension control (r=-0.62, P=0.0007), and CVD mortality (r=0.45, P=0.014), which remained significant after adjusting for economic factors. Conclusions Notable sex disparities remain in CVD prevention and outcomes, with large subgroup heterogeneities. Gendered socioeconomic factors could reinforce such disparities. A sex-specific perspective factoring in socioeconomic disadvantages could facilitate more targeted prevention policy making.

mtPGS: Leverage multiple correlated traits for accurate polygenic score construction

Accurate polygenic scores (PGSs) facilitate the genetic prediction of complex traits and aid in the development of personalized medicine. Here, we develop a statistical method called multi-trait assisted PGS (mtPGS), which can construct accurate PGSs for a target trait of interest by leveraging multiple traits relevant to the target trait. Specifically, mtPGS borrows SNP effect size similarity information between the target trait and its relevant traits to improve the effect size estimation on the target trait, thus achieving accurate PGSs. In the process, mtPGS flexibly models the shared genetic architecture between the target and the relevant traits to achieve robust performance, while explicitly accounting for the environmental covariance among them to accommodate different study designs with various sample overlap patterns. In addition, mtPGS uses only summary statistics as input and relies on a deterministic algorithm with several algebraic techniques for scalable computation. We evaluate the performance of mtPGS through comprehensive simulations and applications to 25 traits in the UK Biobank, where in the real data mtPGS achieves an average of 0.90%-52.91% accuracy gain compared to the state-of-the-art PGS methods. Overall, mtPGS represents an accurate, fast, and robust solution for PGS construction in biobank-scale datasets.

Association between fresh fruit consumption and the risk of chronic obstructive pulmonary disease-related hospitalization and death in Chinese adults: A prospective cohort study

BACKGROUND

Existing evidence suggests that fruit consumption is a significant influencing factor for chronic obstructive pulmonary disease (COPD), but this is unclear in the Chinese population. We examined the association of fresh fruit consumption with the risk of COPD-related hospitalization and death in a nationwide, population-based prospective cohort from China.

METHODS

Between 2004 and 2008, the China Kadoorie Biobank recruited >0.5 million adults aged 30 to 79 years from ten diverse regions across China. After excluding individuals diagnosed with major chronic diseases and prevalent COPD, the prospective analysis included 421,428 participants. Cox regression was used to calculate the hazard ratios (HRs) for the association between fresh fruit consumption and risk of COPD-related hospitalization and death, with adjustment for established and potential confounders.

RESULTS

During a mean follow-up of 10.9 years, 11,292 COPD hospitalization events and deaths were documented, with an overall incidence rate of 2.47/1000 person-years. Participants who consumed fresh fruit daily had a 22% lower risk of COPD-related hospitalization and death compared with non-consumers (HR = 0.78, 95% confidence interval [CI]: 0.71-0.87). The inverse association between fresh fruit consumption and COPD-related hospitalization and death was stronger among non-current smokers and participants with normal body mass index (BMI) (18.5 kg/m 2 ≤ BMI < 24.0 kg/m 2 ); the corresponding HRs for daily fresh fruit consumption were 0.78 (95% CI: 0.68-0.89) and 0.69 (95% CI: 0.59-0.79) compared with their counterparts, respectively.

CONCLUSIONS

High-frequency fruit consumption was associated with a lower risk of COPD in Chinese adults. Increasing fruit consumption, together with cigarette cessation and weight control, should be considered in the prevention and management of COPD.

Association of Leisure-Time Physical Activity and Mortality Risk in High Cardiovascular Risk Population with and without Left Ventricular Hypertrophy

Background

Increased leisure-time physical activity (LTPA) is linked with decreased mortality risk, while also with increased left ventricular mass, which may induce left ventricular hypertrophy (LVH). We investigated whether LVH modifies the association between higher LTPA and lower mortality risk in population at high cardiovascular risk.

Methods

In a prospective national cohort, we used the left ventricular mass/body surface area (LVM/BSA) method to define LVH. Baseline LTPA was self-reported and divided into: low ( < 500 metabolic equivalent of task [MET]) min/week), moderate (500-1999 MET min/week) and high ( ≥ 2000 MET-min/week). Analyses of the dose-response relationship between LTPA and left ventricular mass were performed using restricted cubic spline regression. A multivariate adjusted Cox proportional hazards regression analysis was used to estimate hazard ratios (HRs).

Results

A total of 163,006 participants (55.3% females, mean [standard deviation] age, 62.4 [7.4] years) were included. During a median of 4.8 years of follow-up, 6586 (4.0%) died from all causes and 3024 (1.9%) from cardiovascular causes. Multivariate adjusted Cox proportional hazards regression analyses revealed that moderate and high LTPA were linked with less cardiovascular and all-cause mortality risk than low LTPA in the absence of LVH. In those with LVH, the association of high (0.83, 0.69-0.99) or moderate (0.72, 0.56-0.91) LTPA with cardiovascular mortality risk persisted. For all-cause mortality risk, this association was only significant in high LTPA (0.73, 0.61-0.86), while marginal in moderate LTPA (0.96, 0.84 to 1.08). Overall, the correlation patterns between LTPA and mortality risk appears distinct between those with LVH and those without LVH; the modification of LVH was not significant regarding mortality risk among the high cardiovascular risk population (all-cause: p-value for interaction = 0.074; cardiovascular cause: p-value for interaction = 0.581), except in females regarding all-cause mortality risk (p-value for interaction = 0.006).

Conclusions

The association between higher LTPA and lower mortality risk was not modified by LVH in high cardiovascular risk population. However, the presence of LVH altered this association in females regarding the all-cause mortality risk.

Genome-wide polygenic risk score, cardiometabolic risk factors, and type 2 diabetes mellitus in the Chinese population

OBJECTIVE

Type 2 diabetes (T2D) is caused by both genetic and cardiometabolic risk factors. However, the magnitude of the genetic predisposition of T2D in the Chinese population remains largely unknown.

METHODS

This study included 93,488 participants from the China Kadoorie Biobank, and multiple polygenic risk scores (PRS) were calculated. A common cardiometabolic risk score (CRS) using smoking, alcohol consumption, physical activity, diet, obesity, blood pressure, and blood lipids was constructed to investigate the effects of cardiometabolic risk factors on T2D. Furthermore, an equation based on ideal PRS, CRS, and their interaction was established to explore the combined effects on T2D.

RESULTS

An ideally fitting PRS model (variance explained, R2  = 7.6%) was reached based on multiple PRS calculation methods. An additive interaction between PRS and CRS (coefficient = 28%, 95% CI: 0.20-0.36, p < 0.001) was found. The R2 of the T2D predictive model could increase to 8.3% when CRS and the interaction terms of PRS × CRS were considered. In the etiological composition of T2D, the ratio of genetic risk effect, cardiometabolic risk effect, and interaction between genetic and cardiometabolic factors was 67:16:17.

CONCLUSIONS

This study identified an ideally fitting PRS model for identifying and predicting the risk of T2D suitable for the Chinese population. The quantified proportional structure of genetic risk factors, cardiometabolic risk factors, and their interaction was detected, which elucidated the critical effect of genetic factors.

Conventional and genetic associations of adiposity with 1463 proteins in relatively lean Chinese adults

Adiposity is associated with multiple diseases and traits, but little is known about the causal relevance and mechanisms underlying these associations. Large-scale proteomic profiling, especially when integrated with genetic data, can clarify mechanisms linking adiposity with disease outcomes. We examined the associations of adiposity with plasma levels of 1463 proteins in 3977 Chinese adults, using measured and genetically-instrumented BMI. We further used two-sample bi-directional MR analyses to assess if certain proteins influenced adiposity, along with other (e.g. enrichment) analyses to clarify possible mechanisms underlying the observed associations. Overall, the mean (SD) baseline BMI was 23.9 (3.3) kg/m2, with only 6% being obese (i.e. BMI ≥ 30 kg/m2). Measured and genetically-instrumented BMI was significantly associated at FDR < 0.05 with levels of 1096 (positive/inverse: 826/270) and 307 (positive/inverse: 270/37) proteins, respectively, with FABP4, LEP, IL1RN, LSP1, GOLM2, TNFRSF6B, and ADAMTS15 showing the strongest positive and PON3, NCAN, LEPR, IGFBP2 and MOG showing the strongest inverse genetic associations. These associations were largely linear, in adiposity-to-protein direction, and replicated (> 90%) in Europeans of UKB (mean BMI 27.4 kg/m2). Enrichment analyses of the top > 50 BMI-associated proteins demonstrated their involvement in atherosclerosis, lipid metabolism, tumour progression and inflammation. Two-sample bi-directional MR analyses using cis-pQTLs identified in CKB GWAS found eight proteins (ITIH3, LRP11, SCAMP3, NUDT5, OGN, EFEMP1, TXNDC15, PRDX6) significantly affect levels of BMI, with NUDT5 also showing bi-directional association. The findings among relatively lean Chinese adults identified novel pathways by which adiposity may increase disease risks and novel potential targets for treatment of obesity and obesity-related diseases.

Sleep duration and risk of stroke and coronary heart disease: a 9-year community-based prospective study of 0.5 million Chinese adults

BACKGROUND

There is uncertainty about the optimum sleep duration for risk of different subtypes of stroke and ischaemic heart disease.

METHODS

The present analyses involved 409,156 adults in the China Kadoorie Biobank study without a prior history of coronary heart disease or stroke or insomnia symptoms. The mean age of study participants was 52 years and 59% were women. Self-reported sleep duration including daytime napping was recorded using a questionnaire. The adjusted hazard ratios (HRs) for disease outcomes associated with sleep duration were estimated by Cox proportional hazards after adjustment for confounding factors.

RESULTS

The overall mean (SD) sleep duration was 7.4 (1.4) hours. The associations of sleep duration with CVD types were U-shaped, with individuals reporting 7-8 h of sleep having the lowest risks. Compared with those who typically slept 7-8 h, individuals with very short sleep duration (≤ 5 h) had adjusted HRs of 1.10 (95% CI 1.04-1.16), 1.07 (1.01-1.13), 1.19 (1.06-1.33) and 1.23 (1.10-1.37) for total stroke, ischaemic stroke (IS), Intracerebral haemorrhage (ICH) and major coronary events (MCE), respectively. Likewise, individuals with very long sleep duration (≥ 10 h) had HRs of 1.12 (1.07-1.17), 1.08 (1.03-1.14), 1.23 (1.12-1.35) and 1.22 (1.10-1.34) for the same diseases, respectively, with little differences by sex and age. The patterns were similar for all-cause mortality.

CONCLUSIONS

While abnormal sleep duration (≤ 6 h or ≥ 9 h) was associated with higher risks of CVD, the risks were more extreme for those reporting ≤ 5 or ≥ 10 h, respectively and such individuals should be prioritised for more intensive treatment for CVD prevention.

bubbleHeatmap: an R package for visualization of nightingale health metabolomics datasets

Summary

We present bubbleHeatmap, an R plotting package which combines elements of a bubble plot and heatmap to conveniently display two numerical variables for each data point across a categorical two dimensional grid. This has particular advantages for visualizing the 251 metabolomic measures produced by the automated, high-throughput, 1H-NMR-based platform provided by Nightingale Health, which includes 12 measures repeated across each of 14 lipoprotein subclasses. As these metabolomic profiles are currently available for large biobanks, we provide a figure template to aid the use of bubbleHeatmap in displaying results from analyses using these data.

Availability and implementation

https://cran.r-project.org/web/packages/bubbleHeatmap.

Polygenic scores in cancer

Since the publication of the first genome-wide association study for cancer in 2007, thousands of common alleles that are associated with the risk of cancer have been identified. The relative risk associated with individual variants is small and of limited clinical significance. However, the combined effect of multiple risk variants as captured by polygenic scores (PGSs) may be much greater and therefore provide risk discrimination that is clinically useful. We review the considerable research efforts over the past 15 years for developing statistical methods for PGSs and their application in large-scale genome-wide association studies to develop PGSs for various cancers. We review the predictive performance of these PGSs and the multiple challenges currently limiting the clinical application of PGSs. Despite this, PGSs are beginning to be incorporated into clinical multifactorial risk prediction models to stratify risk in both clinical trials and clinical implementation studies.

Healthy lifestyle and life expectancy free of major chronic diseases at age 40 in China

Whether a healthy lifestyle helps achieve gains in life expectancy (LE) free of major non-communicable diseases and its share of total LE in Chinese adults remains unknown. We considered five low-risk lifestyle factors: never smoking or quitting for reasons other than illness, no excessive alcohol use, being physically active, healthy eating habits and healthy body fat levels. Here we show that after a median follow-up of 11.1 years for 451,233 Chinese adults, the LE free of cardiovascular diseases, cancer and chronic respiratory diseases (95% confidence interval) at age 40 years for individuals with all five low-risk factors was on average 6.3 (5.1-7.5) years (men) and 4.2 (3.6-5.4) years (women) longer than those with 0-1 low-risk factors. Correspondingly, the proportion of disease-free LE to total LE increased from 73.1% to 76.3% for men and from 67.6% to 68.4% for women. Our findings suggest that promoting healthy lifestyles could be associated with gains in disease-free LE in the Chinese population.

Associations of polygenic risk scores with risks of stroke and its subtypes in Chinese

BACKGROUND AND PURPOSE

Previous studies, mostly focusing on the European population, have reported polygenic risk scores (PRSs) might achieve risk stratification of stroke. We aimed to examine the association strengths of PRSs with risks of stroke and its subtypes in the Chinese population.

METHODS

Participants with genome-wide genotypic data in China Kadoorie Biobank were split into a potential training set (n=22 191) and a population-based testing set (n=72 150). Four previously developed PRSs were included, and new PRSs for stroke and its subtypes were developed. The PRSs showing the strongest association with risks of stroke or its subtypes in the training set were further evaluated in the testing set. Cox proportional hazards regression models were used to estimate the association strengths of different PRSs with risks of stroke and its subtypes (ischaemic stroke (IS), intracerebral haemorrhage (ICH) and subarachnoid haemorrhage (SAH)).

RESULTS

In the testing set, during 872 919 person-years of follow-up, 8514 incident stroke events were documented. The PRSs of any stroke (AS) and IS were both positively associated with risks of AS, IS and ICH (p<0.05). The HR for per SD increment (HRSD) of PRSAS was 1.10 (95% CI 1.07 to 1.12), 1.10 (95% CI 1.07 to 1.12) and 1.13 (95% CI 1.07 to 1.20) for AS, IS and ICH, respectively. The corresponding HRSD of PRSIS was 1.08 (95% CI 1.06 to 1.11), 1.08 (95% CI 1.06 to 1.11) and 1.09 (95% CI 1.03 to 1.15). PRSICH was positively associated with the risk of ICH (HRSD=1.07, 95% CI 1.01 to 1.14). PRSSAH was not associated with risks of stroke and its subtypes. The addition of current PRSs offered little to no improvement in stroke risk prediction and risk stratification.

CONCLUSIONS

In this Chinese population, the association strengths of current PRSs with risks of stroke and its subtypes were moderate, suggesting a limited value for improving risk prediction over traditional risk factors in the context of current genome-wide association study under-representing the East Asian population.

Methods for Assessing Population Relationships and History Using Genomic Data

Genetic data contain a record of our evolutionary history. The availability of large-scale datasets of human populations from various geographic areas and timescales, coupled with advances in the computational methods to analyze these data, has transformed our ability to use genetic data to learn about our evolutionary past. Here, we review some of the widely used statistical methods to explore and characterize population relationships and history using genomic data. We describe the intuition behind commonly used approaches, their interpretation, and important limitations. For illustration, we apply some of these techniques to genome-wide autosomal data from 929 individuals representing 53 worldwide populations that are part of the Human Genome Diversity Project. Finally, we discuss the new frontiers in genomic methods to learn about population history. In sum, this review highlights the power (and limitations) of DNA to infer features of human evolutionary history, complementing the knowledge gleaned from other disciplines, such as archaeology, anthropology, and linguistics.

The All of Us Data and Research Center: Creating a Secure, Scalable, and Sustainable Ecosystem for Biomedical Research

The All of Us Research Program's Data and Research Center (DRC) was established to help acquire, curate, and provide access to one of the world's largest and most diverse datasets for precision medicine research. Already, over 500,000 participants are enrolled in All of Us, 80% of whom are underrepresented in biomedical research, and data are being analyzed by a community of over 2,300 researchers. The DRC created this thriving data ecosystem by collaborating with engaged participants, innovative program partners, and empowered researchers. In this review, we first describe how the DRC is organized to meet the needs of this broad group of stakeholders. We then outline guiding principles, common challenges, and innovative approaches used to build the All of Us data ecosystem. Finally, we share lessons learned to help others navigate important decisions and trade-offs in building a modern biomedical data platform.

Topic modeling identifies novel genetic loci associated with multimorbidities in UK Biobank

Many diseases show patterns of co-occurrence, possibly driven by systemic dysregulation of underlying processes affecting multiple traits. We have developed a method (treeLFA) for identifying such multimorbidities from routine health-care data, which combines topic modeling with an informative prior derived from medical ontology. We apply treeLFA to UK Biobank data and identify a variety of topics representing multimorbidity clusters, including a healthy topic. We find that loci identified using topic weights as traits in a genome-wide association study (GWAS) analysis, which we validated with a range of approaches, only partially overlap with loci from GWASs on constituent single diseases. We also show that treeLFA improves upon existing methods like latent Dirichlet allocation in various ways. Overall, our findings indicate that topic models can characterize multimorbidity patterns and that genetic analysis of these patterns can provide insight into the etiology of complex traits that cannot be determined from the analysis of constituent traits alone.

Genotyping and population characteristics of the China Kadoorie Biobank

The China Kadoorie Biobank (CKB) is a population-based prospective cohort of >512,000 adults recruited from 2004 to 2008 from 10 geographically diverse regions across China. Detailed data from questionnaires and physical measurements were collected at baseline, with additional measurements at three resurveys involving ∼5% of surviving participants. Analyses of genome-wide genotyping, for >100,000 participants using custom-designed Axiom arrays, reveal extensive relatedness, recent consanguinity, and signatures reflecting large-scale population movements from recent Chinese history. Systematic genome-wide association studies of incident disease, captured through electronic linkage to death and disease registries and to the national health insurance system, replicate established disease loci and identify 14 novel disease associations. Together with studies of candidate drug targets and disease risk factors and contributions to international genetics consortia, these demonstrate the breadth, depth, and quality of the CKB data. Ongoing high-throughput omics assays of collected biosamples and planned whole-genome sequencing will further enhance the scientific value of this biobank.

Helicobacter pylori multiplex serology and risk of non-cardia and cardia gastric cancer: a case-cohort study and meta-analysis

BACKGROUND

Helicobacter pylori infection is a major cause of non-cardia gastric cancer (NCGC), but uncertainty remains about the associations between sero-positivity to different H. pylori antigens and risk of NCGC and cardia gastric cancer (CGC) in different populations.

METHODS

A case-cohort study in China included ∼500 each of incident NCGC and CGC cases and ∼2000 subcohort participants. Sero-positivity to 12 H. pylori antigens was measured in baseline plasma samples using a multiplex assay. Hazard ratios (HRs) of NCGC and CGC for each marker were estimated using Cox regression. These were further meta-analysed with studies using same assay.

RESULTS

In the subcohort, sero-positivity for 12 H. pylori antigens varied from 11.4% (HpaA) to 70.8% (CagA). Overall, 10 antigens showed significant associations with risk of NCGC (adjusted HRs: 1.33 to 4.15), and four antigens with CGC (HRs: 1.50 to 2.34). After simultaneous adjustment for other antigens, positive associations remained significant for NCGC (CagA, HP1564, HP0305) and CGC (CagA, HP1564, HyuA). Compared with CagA sero-positive only individuals, those who were positive for all three antigens had an adjusted HR of 5.59 (95% CI 4.68-6.66) for NCGC and 2.17 (95% CI 1.54-3.05) for CGC. In the meta-analysis of NCGC, the pooled relative risk for CagA was 2.96 (95% CI 2.58-3.41) [Europeans: 5.32 (95% CI 4.05-6.99); Asians: 2.41 (95% CI 2.05-2.83); Pheterogeneity<0.0001]. Similar pronounced population differences were also evident for GroEL, HP1564, HcpC and HP0305. In meta-analyses of CGC, two antigens (CagA, HP1564) were significantly associated with a higher risk in Asians but not Europeans.

CONCLUSIONS

Sero-positivity to several H. pylori antigens was significantly associated with an increased risk of NCGC and CGC, with varying effects between Asian and European populations.

Lung cancer risk score for ever and never smokers in China

BACKGROUND

Most lung cancer risk prediction models were developed in European and North-American cohorts of smokers aged ≥ 55 years, while less is known about risk profiles in Asia, especially for never smokers or individuals aged < 50 years. Hence, we aimed to develop and validate a lung cancer risk estimate tool for ever and never smokers across a wide age range.

METHODS

Based on the China Kadoorie Biobank cohort, we first systematically selected the predictors and explored the nonlinear association of predictors with lung cancer risk using restricted cubic splines. Then, we separately developed risk prediction models to construct a lung cancer risk score (LCRS) in 159,715 ever smokers and 336,526 never smokers. The LCRS was further validated in an independent cohort over a median follow-up of 13.6 years, consisting of 14,153 never smokers and 5,890 ever smokers.

RESULTS

A total of 13 and 9 routinely available predictors were identified for ever and never smokers, respectively. Of these predictors, cigarettes per day and quit years showed nonlinear associations with lung cancer risk (Pnon-linear < 0.001). The curve of lung cancer incidence increased rapidly above 20 cigarettes per day and then was relatively flat until approximately 30 cigarettes per day. We also observed that lung cancer risk declined sharply within the first 5 years of quitting, and then continued to decrease but at a slower rate in the subsequent years. The 6-year area under the receiver operating curve for the ever and never smokers' models were respectively 0.778 and 0.733 in the derivation cohort, and 0.774 and 0.759 in the validation cohort. In the validation cohort, the 10-year cumulative incidence of lung cancer was 0.39% and 2.57% for ever smokers with low (< 166.2) and intermediate-high LCRS (≥ 166.2), respectively. Never smokers with a high LCRS (≥ 21.2) had a higher 10-year cumulative incidence rate than those with a low LCRS (< 21.2; 1.05% vs. 0.22%). An online risk evaluation tool (LCKEY; http://ccra.njmu.edu.cn/lckey/web) was developed to facilitate the use of LCRS.

CONCLUSIONS

The LCRS can be an effective risk assessment tool designed for ever and never smokers aged 30 to 80 years.